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Ziwen Pan; Yongliang Wang – European Journal of Education, 2025
Artificial Intelligence (AI) literacy has come to the spotlight, empowering individuals to adeptly navigate the modern digitalised world. However, studies on teacher AI literacy in the English as a Foreign Language (EFL) context remain limited. This study aims to identify intraindividual differences in AI literacy and examine its associations with…
Descriptors: Technological Literacy, Artificial Intelligence, Language Teachers, Second Language Instruction
Mo Zhang; Paul Deane; Andrew Hoang; Hongwen Guo; Chen Li – Educational Measurement: Issues and Practice, 2025
In this paper, we describe two empirical studies that demonstrate the application and modeling of keystroke logs in writing assessments. We illustrate two different approaches of modeling differences in writing processes: analysis of mean differences in handcrafted theory-driven features and use of large language models to identify stable personal…
Descriptors: Writing Tests, Computer Assisted Testing, Keyboarding (Data Entry), Writing Processes
Chenghao Wang; Xueyun Li; Bin Zou – European Journal of Education, 2025
Research on the factors influencing the acceptance of GenAI in language learning has expanded widely; however, few studies have focused on the role of language learning emotions. To enhance the effectiveness of GenAI-powered English-speaking instruction and the learning experience, this study expands on the Integrated Model of Technology…
Descriptors: Technology Uses in Education, Technology Integration, Artificial Intelligence, Second Language Learning
Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
Ellana Black; Kristen Betts – Impacting Education: Journal on Transforming Professional Practice, 2025
This convergent mixed methods research study investigated how a small, non-representative sample of Educational Doctorate (EdD) faculty perceive and use generative AI and how they have leveraged the technology to support EdD students. A cross-sectional survey was used to gather data from 27 EdD faculty members to assess their generative AI…
Descriptors: Doctoral Programs, Education Majors, College Faculty, Artificial Intelligence
Yu-Yin Wang – Education and Information Technologies, 2025
Considering the proliferation of artificial intelligence (AI) technologies, it has become crucial to integrate AI-related knowledge and skills education into business management curricula. This is a significant concern for both academics and practitioners. However, in the context of university business management education, few studies have…
Descriptors: Individual Differences, Intention, Artificial Intelligence, Technology Uses in Education
Liwei Hsu – European Journal of Education, 2025
As generative artificial intelligence (GenAI) increasingly penetrates language education, understanding learners' continued intention to use this technology becomes crucial. This study examines EFL learners' continuance intention to use GenAI for language learning through PLS-SEM and fsQCA methodologies. Participants were undergraduate EFL…
Descriptors: Second Language Learning, English (Second Language), Artificial Intelligence, Student Attitudes
Ke Li; Lulu Lun; Pingping Hu – Education and Information Technologies, 2025
Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…
Descriptors: Student Attitudes, Language Attitudes, Affordances, Artificial Intelligence